Datasets are extremely important in many scientific disciplines. They are essential for benchmarking and algorithm comparison, but with the emergence of deep learning, datasets have become the basic support over which the new artificial intelligence is sustained.
For the problem at hand, the variable size of the data and its structured nature is one of the challenges from a learning point of view.
The 9280 samples generated in SocNav1 seem to be enough for machine learning purposes given the size of the data structures describing the scenarios.
Initial results applying the dataset to graph neural networks support this idea [1]}.
